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Mipiti
by Mipiti

add_functional_test

Manually register a functional test and link it to specific security objectives, without running or verifying the test.

Instructions

Hand-author a single functional test and map it to one or more objectives. Mutating.

Generation (generate_functional_objectives) already specifies the tests to implement, so use this only to register an extra test that generation did not produce; a manually-added test survives regeneration/refresh. For bulk-registering tests that already exist in your codebase, use import_functional_tests instead. This records the test at the status you claim — it does not run or verify anything; CI verification happens only when you attach TEST_EXISTS/TEST_PASSES evidence via submit_functional_test_assertions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNonot_implemented | implemented | verified — an operator claim only; an independent CI run is what actually verifies the test. Defaults to not_implemented.not_implemented
model_idYesID of the threat model.
descriptionYesWhat the test proves.
component_idsNoComma-separated component ids the test exercises (optional).
server_versionYes
functional_objective_idsYesComma-separated objective ids the test satisfies (at least one required; get them from get_functional_objectives).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It transparently states that this tool does not run or verify tests and that the status is only a claim, with verification occurring later via submit_functional_test_assertions. This is excellent disclosure of behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, using two sentences to convey purpose, usage guidance, and behavioral caveats without any fluff or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool that manually adds a test, the description covers its purpose, when to use it, and its non-verification nature. It is complete enough for an agent to decide when and how to invoke it appropriately.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description does not elaborate on parameter meanings. The schema already provides descriptions for most parameters (though server_version lacks one), but the tool description adds no extra context about the parameters themselves, leaving them to the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: to hand-author a single functional test and map it to objectives. It distinguishes itself from generation and import tools, making its purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly explains when to use this tool versus alternatives: use it for manually adding a test that generation did not produce, and use import for bulk-registering existing tests. This provides clear usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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